Analysis of Sectoral Energy Demand in Pakistan

Purpose This research aims to estimate the energy demand for different sectors, including commercial, industrial, residential, transportation, and agriculture. For this purpose, various factors affecting the demand for energy in each sector have been analyzed. Methodology The adopted methodology is box Jenkins a systematic approach of identification, estimation, diagnostic checks, and forecasting of the model. This model is appropriate for time series data of medium to long-term length. Findings The data analysis outcomes specified that Pakistan's energy demand mainly depends on five fuel types. Within each sector, the consumption of fuel varies. Results show that 86% of energy consumption share is held by transport oil, industrial gas, industrial coal, residential gas, and residential electricity. Conclusion The major issue in the energy sector is the demand-supply gap primarily caused by the gas and electricity deficit. Conclusively, sectoral demand increases in each sector where commercial, residential, and industrial energy demand has higher growth. Moreover, the price effect is negative for all variables except coal, making it a Giffen goo

Dynamic Load Sharing at Domestic Level Using the Internet of Things

At the domestic level, load management plays a vital role as the consumer line gets overloaded due to the various load categories. The fully loaded line consumes more energy units, which increases the electricity bill of the consumer. To circumvent the issue of load unbalancing, an automated load management system is developed that shifts the load from one line to another. The proposed system is developed by making use of current and potential sensing transformers and the Arduino Mega board. Moreover, the proposed system also provides an internet of things (IoT) based monitoring facility to the user. The sensed information from the system is uploaded to the webserver with the help of Wireless Fidelity (Wi-Fi) from where the user can access this information at any time through appropriate applications. Based on the monitoring data, the user can take necessary decisions regarding switching off unnecessary load. Both simulation and hardware results demonstrate the effectiveness of the proposed system

Comparison of surface defects in Protaper Next and Hyflex EDM files after single clinical use: A stereoscopic evaluation

Objective: To compare the surface defects created on the ProTaper Next files versus HyFlex Electrical Discharge Machining files after single clinical use in molars.Methods: The cross-sectional study was conducted in the dental department of the Aga Khan University Hospital, Karachi, from December 2018 to June 2019, and comprised Nickel-Titanium files belonging to HyFlex Electrical Discharge Machining and ProTaper Next to perform complete root canal treatment of molar teeth. The files were first visually examined and then analysed under 25.6x magnification using a stereomicroscope for the evaluation of surface defects. A photographic record was maintained and studied. Data was analysed using SPSS 23.0.Results: Of the 114 files, 38(33.3%) each were ProTaper Next X1, ProTaper Next X2 and HyFlex Electrical Discharge Machining. The number of files showing defects under microscopic evaluation were 17(14.9%). Deformation of the cutting edge was the most frequently seen defect type, found in 9(7.9%) files. The frequency of fractured files was 4(3.5%). The odds of microscopic defects in HyFlex Electrical Discharge Machining files was 2.64 times that of ProTaper Next files.Conclusion: Even after single clinical use, HyFlex Electrical Discharge Machining files were more likely to get microscopic defects on their surface compared to ProTaper files

Load Management System with Integration of Renewable Energy Resources

This article presents, a load management system is designed and implemented to integrate renewable energy resources (RES) (solar and wind), which manage the load according to the supply/demand and the user's priorities. The system is implemented on a hybrid system integrating wind energy, solar energy, utility supply, and battery energy storage system. Load management is carried out via switching of the loads. The sources can also be turned ON and OFF. During excess power, the battery module works as an energy storage unit or backup energy supply unit during demand. Loads can be turned ON and OFF wirelessly via GSM. The grid operator can switch the loads by simply sending a command via a short service message (SMS). In the end, the system is tested, and the results are presented.   The hybrid system is simulated in MATLAB/Simulink first and then hardware implementation is carried out, which involves integrating renewable resources via converters and load management by switching using a microcontroller (Arduino)

Synthesis and Characterization of Graphene sheets from graphite powder by using ball milling

Due to the rising trend in 2-Dimensional material, graphene has gained a lot of interest in the recent past. Graphene is the 2D carbon allotrope with high strength and improved mechanical, chemical, and electrical properties. Despite being excellent properties among other types of carbon allotropes but still, graphene use is limited because of its costly synthesis technique. In this research, a cheap and effective method is adapted for the preparation of graphene from graphite powder. The graphite powder is thermally treated to prepare the exfoliated graphite then exfoliated graphite is milled to produce the 2D graphene sheets. The synthesized graphene is characterized by X-Ray Diffractometry (XRD) and Scanning Electron Microscope (SEM). The XRD results show that graphene is successfully synthesized, and SEM results show that graphene is 2D which can be used in various applications. This research provides a direction for the synthesis of graphene from graphite powder on an industrial scale.Debido a la tendencia al alza en el material bidimensional, el grafeno ha ganado mucho interés en el pasado reciente. El grafeno es el alótropo de carbono 2D con propiedades mecánicas, químicas y eléctricas mejoradas de alta resistencia. A pesar de tener excelentes propiedades entre otros tipos de alótropos de carbono, el uso del grafeno es limitado debido a su costosa técnica de síntesis. En esta investigación se adapta un método económico y efectivo para la preparación de grafeno a partir de polvo de grafito. El polvo de grafito se trata térmicamente para preparar el grafito exfoliado y luego se muele para producir las láminas de grafeno 2D. El grafeno sintetizado se caracteriza por difractometría de rayos X (XRD) y microscopio electrónico de barrido (SEM). Los resultados de XRD muestran que el grafeno se sintetiza con éxito y los resultados de SEM muestran que el grafeno es 2D que se puede usar en varias aplicaciones. Esta investigación proporciona una dirección para la síntesis de grafeno a partir de polvo de grafito a escala industrial

Predicting Divorce Prospect Using Ensemble Learning:Support Vector Machine, Linear Model, and Neural Network

A divorce is a legal step taken by married people to end their marriage. It occurs after a couple decides to no longer live together as husband and wife. Globally, the divorce rate has more than doubled from 1970 until 2008, with divorces per 1,000 married people rising from 2.6 to 5.5. Divorce occurs at a rate of 16.9 per 1,000 married women. According to the experts, over half of all marriages ends in divorce or separation in the United States. A novel ensemble learning technique based on advanced machine learning algorithms is proposed in this study. The support vector machine (SVM), passive aggressive classifier, and neural network (MLP) are applied in the context of divorce prediction. A question-based dataset is created by the field specialist. The responses to the questions provide important information about whether a marriage is likely to turn into divorce in the future. The cross-validation is applied in 5 folds, and the performance results of the evaluation metrics are examined. The accuracy score is 100%, and Receiver Operating Characteristic (ROC) curve accuracy score, recall score, the precision score, and the F1 accuracy score are close to 97% confidently. Our findings examined the key indicators for divorce and the factors that are most significant when predicting the divorce

Concept mapping and conceptual change texts: a constructivist approach to address the misconceptions in nanoscale science and technology

Nanoscale Science and Technology (NST) is a rapidly evolving field with profound implications for various industries and our everyday lives. However, misconceptions among learners can hinder their ability to grasp the fundamental concepts of NST, thereby impeding their potential contributions to this advancing domain. Concept maps (CM) and conceptual change texts (CCT) are graphical and written representations of knowledge that enable learners to visualize relationships between concepts and assess the coherence of their understanding. In this pursuit, we engage with the concept of rehabilitation for misconceptions, viewing the learning process as a transformative journey akin to cognitive rehabilitation. Through this CM-CCT constructivist approach, learners are encouraged to engage in critical reflection, self-questioning, and peer discussions, which facilitate the identification of misconceptions. Moreover, CM-CCT provide a structured framework for presenting accurate information about NST, offering a clear depiction of the hierarchical and interconnected nature of nanoscale phenomena. The aim of this study was to evaluate the effectiveness of CM-CCT in correcting the misconceptions of undergraduate university students regarding nanotechnology and the taxonomy of nonmaterial. Prior to the implementation of the CM-CCT, an assessment of pre-existing knowledge of the students was performed through the structure of the observed learning outcomes (SOLO) taxonomy. A quasi-experimental research design was carried out. A total of 70 undergraduate university students, divided into two intact groups, were cross-examined for the study. Further, before and after the instructional tools, an achievement test based on nanotechnology and classification of nonmaterial was conducted, covering all six cognitive domains of the Bloom taxonomy of educational objectives. Data analysis revealed that the instructional tools based on constructivist approach had a statistically significant impact on students for elimination of their misconceptions about nanotechnology, nano science and classification of nonmaterial

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation